Daynamica UCAL Visualization Report
Daynamica Team
2024-04-26
library(dplyr)
library(ggplot2)
source('../helper_functions/s4_temporal_plot.R')
library(lubridate)
library(ggnewscale)
library(wesanderson)
daynamica_data <- params$daynamica_data
if(is.null(params$color_codings)){
unique_activity_labels <-
daynamica_data$ucalitems_temporal_plot %>%
tibble() %>%
filter(type_decoded == "ACTIVITY") %>%
pull(subtype_decoded) %>% unique()
unique_trip_labels <-
daynamica_data$ucalitems_temporal_plot %>%
tibble() %>%
filter(type_decoded == "TRIP") %>%
pull(subtype_decoded) %>% unique()
activity_palette <- c(wes_palette("Zissou1", 1),
wes_palette("Zissou1", 5)[4:5],
rev(wes_palette("Royal1", 4)[2:4]),
wes_palette("Moonrise3", 2),
wes_palette("GrandBudapest2"),
wes_palette("GrandBudapest1"),
wes_palette("Chevalier1", 4))[1:length(unique_activity_labels)]
trip_palette <- c(palette.colors(n = 8, "ggplot2")[-1],
palette.colors(n = 8, "alphabet"))[1:length(unique_trip_labels)]
color_codes_activity_data <- data.frame(labels = unique_activity_labels,
values = activity_palette)
color_codes_trips_data <- data.frame(labels = unique_trip_labels,
values = trip_palette)
}else{
color_codes_activity_data <- params$color_codings$color_codes_activity_data
color_codes_trips_data <- params$color_codings$color_codes_trips_data
}
if(is.null(params$limit_tod)){
min_time = 0
max_time = 1
} else{
min_time <- limit_tod[1]
max_time <- limit_tod[2]
}Visualization Notes
These plots show 7-day views of the calendar item data collected via the Daynamica app. Each figure starts on a Sunday. For participants who collected data for longer than one week, there will be multiple plots which can be accessed via separate tabs.
Colors and Category levels can be modified via dataset manipulations and report parameters. See the master_analysis_file.R for further details.
User Calendar Item Visualizations
pages <- ceiling(length(user_id_list) /10)
user_id_list_short <- sub("@[^@]*$", "", user_id_list)
for(i in 1:pages){
if(i != pages){
id_index <- (1 + 10*(i-1)):(10 + 10*(i-1))
} else{
id_index <-(1 + 10*(i-1)):length(user_id_list)
}
cat("\n\n## Participants: ", min(id_index), "-", max(id_index), " {.tabset} \n")
for(j in id_index){
cat("\n\n### ", user_id_list_short[j], " {.tabset} \n")
#print(user_id_list_short[j])
temp_data <- daynamica_data$ucalitems_temporal_plot %>%
as_tibble() %>%
filter(user_id == user_id_list[j])
tab <- tibble(start_date = as.Date(min(temp_data$start_date):max(temp_data$start_date), origin = "1970-01-01"),
day_number = lubridate::wday(start_date),
check = ifelse(day_number == 1, 1, 0),
cum_total = cumsum(check))
# tab <- temp_data %>%
# select(start_date, dow) %>%
# mutate(day_number = lubridate::wday(start_date)) %>%
# distinct() %>%
# arrange(start_date) %>%
# mutate(check = ifelse(day_number == 1, 1, 0),
# cum_total = cumsum(check))
unique_weeks <- unique(tab$cum_total)
for(k in 1:length(unique_weeks)){
current_dates <- tab %>%
filter(cum_total == unique_weeks[k])
suppressWarnings(dates_this_week <- as.Date((current_dates$start_date - current_dates$day_number + 1) + 0:6, origin = "1970-01-01"))
#tab_text <- paste0(min(current_dates$start_date), " : ", max(current_dates$start_date))
tab_text <- paste0(min(dates_this_week), " : ", max(dates_this_week))
cat("\n\n#### ", tab_text, " \n")
analysis_data <- temp_data %>%
filter(start_date %in% dates_this_week)
if(nrow(analysis_data) == 0){
print("No data during this date range")
next
}
analysis_data <- analysis_data %>%
bind_rows(analysis_data[rep(1, 7),] %>% # This code allows all days of the week to be displayed even if we don't have data on those dates.
mutate(start_time = "04:00:00",
end_time = "04:00:01",
start_date = dates_this_week,
type_decoded = "ACTIVITY")) %>%
mutate(end_time = ifelse(end_time == "00:00:00", "24:00:00", end_time))
p <- suppressMessages(generate_time_of_day_plot(analysis_data,
color_codes_activity = color_codes_activity_data,
color_codes_trips = color_codes_trips_data,
min_time = min_time,
max_time = max_time)) +
ggtitle(paste0("Calendar Item Visualization: ", user_id_list_short[j]),
subtitle = paste0("Date Range: ", tab_text))
print(p)
}
}
}Participants: 1 - 10
user_id_122
2022-11-13 : 2022-11-19
2022-11-20 : 2022-11-26
2022-11-27 : 2022-12-03
2022-12-04 : 2022-12-10
2022-12-11 : 2022-12-17
2022-12-18 : 2022-12-24
[1] “No data during this date range”
2022-12-25 : 2022-12-31
2023-01-01 : 2023-01-07
user_id_125
2022-12-04 : 2022-12-10
2022-12-11 : 2022-12-17
user_id_13
2022-12-04 : 2022-12-10
2022-12-11 : 2022-12-17
user_id_142
2023-01-01 : 2023-01-07
2023-01-08 : 2023-01-14
user_id_148
2022-12-11 : 2022-12-17
user_id_159
2022-11-13 : 2022-11-19
2022-11-20 : 2022-11-26
2022-11-27 : 2022-12-03
2022-12-04 : 2022-12-10
user_id_165
2023-02-19 : 2023-02-25
2023-02-26 : 2023-03-04
2023-03-05 : 2023-03-11
user_id_17
2022-11-06 : 2022-11-12
2022-11-13 : 2022-11-19
2022-11-20 : 2022-11-26
user_id_192
2023-01-22 : 2023-01-28
user_id_219
2023-01-15 : 2023-01-21
2023-01-22 : 2023-01-28
Participants: 11 - 15
user_id_233
2022-11-13 : 2022-11-19
2022-11-20 : 2022-11-26
user_id_24
2022-12-18 : 2022-12-24
2022-12-25 : 2022-12-31
2023-01-01 : 2023-01-07
user_id_241
2023-01-15 : 2023-01-21
2023-01-22 : 2023-01-28
2023-01-29 : 2023-02-04
user_id_271
2022-10-23 : 2022-10-29
user_id_277
2023-01-15 : 2023-01-21
